Author: Daisuke Matsuyoshi (National Institute for Radiological Sciences (QST-NIRS) and Araya, Inc.)
Implementation of DISTATIS written in MATLAB. DISTATIS is a generalization of classial multidimensional scaling and handles m sets of data tables collected on the same set of n observations, combining datasets into a common consensus structure, called "compromise."
[eigval,eigvector,fscore,eigval3,eigvector3,fscore3] = distatis(data);datashould be a 3D distance (dissimilarity) matrix [n x n x m].- n x n distance matrices stacking along 3rd dimension m times
- For example usage, see
distatis_demo.m
- eigval - Eigenvalues for compromise
- eigvector - Eigenvector for compromise
- fscore - Factor score for compromise
- eigval3 - Eigenvalues for dim 3
- eigvector3 - Eigenvector for dim 3
- fscore3 - Factor score for dim 3
- Abdi H, Toole AJO, Valentin D, Edelman B (2005) DISTATIS: The analysis of multiple distance matrices. IEEE CVPR 2005, 42-47. doi: 10.1109/CVPR.2005.445
- Abdi H, Valentin D, Chollet S, Chrea C (2007) Analyzing assessors and products in sorting tasks: DISTATIS, theory and applications. Food Qual Prefer 18:627-640. doi: 10.1016/j.foodqual.2006.09.003
The DISTATIS_matlab is free but copyright software, distributed under the terms of the BSD 3-Clause "New" or "Revised" License.
Copyright (C) 2020-2022 Daisuke Matsuyoshi
This program is free software: you can redistribute it and/or modify it under the terms of the BSD 3-Clause "New" or "Revised" License.
This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the BSD 3-Clause "New" or "Revised" License for more details.
You should have received a copy of the BSD 3-Clause "New" or "Revised" License along with this program. If not, see https://opensource.org/licenses/BSD-3-Clause.